pandas数据预处理实例

1. 排序，默认从小到大排

   #By default, pandas will sort the data by the column we specify in ascending order and return a new DataFrame
   # Sorts the DataFrame in-place, rather than returning a new DataFrame.
   #print food_info["Sodium_(mg)"]
   food_info.sort_values("Sodium_(mg)", inplace=True)
   print (food_info["Sodium_(mg)"])
   #Sorts by descending order, rather than ascending.
   food_info.sort_values("Sodium_(mg)", inplace=True, ascending=False)
   print (food_info["Sodium_(mg)"])
   

   运行结果：
   

2. 打开一个csv文件

   import pandas as pd
   import numpy as np
   titanic_survival = pd.read_csv("titanic_train.csv")
   titanic_survival.head()
   

   运行结果：
   

3. 计算空值个数

   #The Pandas library uses NaN, which stands for "not a number", to indicate a missing value.
   #we can use the pandas.isnull() function which takes a pandas series and returns a series of True and False values
   age = titanic_survival["Age"]
   # print(age.loc[0:10])
   age_is_null = pd.isnull(age)
   # print (age_is_null)
   age_null_true = age[age_is_null]
   # print (age_null_true)
   age_null_count = len(age_null_true)
   print(age_null_count)
   

   运行结果：